Exploiting time in electronic health record correlations.
about
Innovative information visualization of electronic health record data: a systematic reviewNetwork analysis of unstructured EHR data for clinical researchDynamical phenotyping: using temporal analysis of clinically collected physiologic data to stratify populationsModeling temporal relationships in large scale clinical associationsNonconvulsive seizures after subarachnoid hemorrhage: Multimodal detection and outcomesRediscovering drug side effects: the impact of analytical assumptions on the detection of associations in EHR dataComparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR dataTemporal properties of diagnosis code time series in aggregate.A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records.Identifying and mitigating biases in EHR laboratory tests.Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation.Predictability Bounds of Electronic Health Records.Discovery of prostate specific antigen pattern to predict castration resistant prostate cancer of androgen deprivation therapyDecaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.Next-generation phenotyping of electronic health records.Correlating electronic health record concepts with healthcare process events.Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.Parameterizing time in electronic health record studies.Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.High-fidelity phenotyping: richness and freedom from bias.Inpatient Clinical Order Patterns Machine-Learned From Teaching Versus Attending-Only Medical Services.Illustrating Informed Presence Bias in Electronic Health Records Data: How Patient Interactions with a Health System Can Impact Inference.
P2860
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P2860
Exploiting time in electronic health record correlations.
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Exploiting time in electronic health record correlations.
@ast
Exploiting time in electronic health record correlations.
@en
type
label
Exploiting time in electronic health record correlations.
@ast
Exploiting time in electronic health record correlations.
@en
prefLabel
Exploiting time in electronic health record correlations.
@ast
Exploiting time in electronic health record correlations.
@en
P2860
P1476
Exploiting time in electronic health record correlations.
@en
P2093
Adler Perotte
David J Albers
P2860
P304
P356
10.1136/AMIAJNL-2011-000463
P478
18 Suppl 1
P577
2011-11-23T00:00:00Z